A methodology for territorial distribution of CO₂emission reductions in transport sector

Abstract

SUMMARY Greenhouse gas emission reduction is the pillar of the Kyoto Protocol and one of the main goals of the European Union (UE) energy policy. National reduction targets for EU member states and an overall target for the EU‐15 (8%) were set by the Kyoto Protocol. This reduction target is based on emissions in the reference year (1990) and must be reached by 2012. EU energy policy does not set any national targets, only an overall reduction target of 20% by 2020. This paper transfers global greenhouse gas emission reduction targets in both these documents to the transport sector and specifically to CO2 emissions. It proposes a nonlinear distribution method with objective, dynamic targets for reducing CO2 emissions in the transport sector, according to the context and characteristics of each geographical area. First, we analyse CO2 emissions from transport in the reference year (1990) and their evolution from 1990 to 2007. We then propose a nonlinear methodology for distributing dynamic CO2 emission reduction targets. We have applied the proposed distribution function for 2012 and 2020 at two territorial levels (EU member states and Spanish autonomous regions). The weighted distribution is based on per capita CO2 emissions and CO2 emissions per gross domestic product. Finally, we show the weighted targets found for each EU member state and each Spanish autonomous region, compare them with the real achievements to date, and forecast the situation for the years the Kyoto and EU goals are to be met. The results underline the need for ‘weighted’ decentralised decisions to be made at different territorial levels with a view to achieving a common goal, so relative convergence of all the geographical areas is reached over time. Copyright © 2011 John Wiley & Sons, Ltd.

Projection of Greenhouse Gas Emissions for the Road Transport Sector Based on Multivariate Regression and the Double Exponential Smoothing Model

“…Likewise, Tokunaga and Konan [15] and Konur [16] used panel data to provide estimations of CO 2 from the transportation sector. Tolón-Becerra et al [17] focus on the emission reduction targets of EU countries. A study found a relationship of a co-combination of fuel price (FP) and pay per capita on transport fuel consumption (FC) [18].…”

Application of a Adaptive Neuro-Fuzzy Technique for Projection of the Greenhouse Gas Emissions from Road Transportation

“…Furthermore, panel data has been used by Tokunaga and Konan [31] and Konur [32], in order to provide estimations of CO 2 which are caused by the transportation sector. Moreover, Tolón-Becerra and Pérez-Martínez [33] focus on the targets set by EU countries towards the reduction of CO 2 emissions. Sultan [34] was able to find out that there existed a co-combination of fuel price (FP) and pay per capita on transport fuel consumption (FC).…”

Geochemical modeling of changes in caprock permeability caused by CO2–brine–rock interactions under the diffusion mechanism

“…In TOUGHREACT, for the rock matrix, it is given as a relation to porosity, using a simplified form of the Carman-Kozeny equations (1) and (2). Matrix permeability changes are calculated from changes in porosity using ratios of permeability calculated from the Carman-Kozeny relation, and ignoring changes in grain size, tortuosity and specific surface area as follows [30]:…”

“…Greenhouse effect mainly due to anthropogenic CO 2 emissions has caused a series of global environmental problems, CO 2 emission reduction has become hot issues of general concern [1][2][3]. It is generally accepted that CO 2 geological storage is the most promising method for reducing atmospheric CO 2 emissions [4][5][6][7][8].…”